Standardized estimates from categorical regression models.

Abstract

We consider the problem of interpreting categorical regression models, such as the polytomous logistic model, the continuation-ratio model, the stereotype model, and the cumulative-odds model. We present a method to convert categorical regression coefficients into estimates of standardized fitted probabilities, probability differences and probability ratios. We use a delta-method approach to estimate standard errors. We then present a small simulation study to compare different transforms for setting confidence limits, and provide an illustration of our approach in an observational study of drug therapy of polymyositis.

• Authors: M M Joffe, S Greenland
• Journal: Statistics in medicine (Stat Med) Vol. 14 Issue 19 Pg. 2131-41 (Oct 15 1995) ISSN: 0277-6715 [Print] England
• PMID: 8552892 (Publication Type: Clinical Trial, Controlled Clinical Trial, Journal Article, Research Support, U.S. Gov't, P.H.S.)

Chemical References

• Anti-Inflammatory Agents
• Autoantibodies
• Immunosuppressive Agents
• Azathioprine
• Prednisone

Topics

• Algorithms
• Anti-Inflammatory Agents (immunology)
• Autoantibodies (immunology)
• Azathioprine (immunology)
• Confidence Intervals
• Confounding Factors, Epidemiologic
• Data Interpretation, Statistical
• Humans
• Immunosuppressive Agents (immunology)
• Models, Statistical
• Odds Ratio
• Polymyositis (drug therapy)
• Prednisone (immunology)
• Regression Analysis
• Statistics, Nonparametric
• Treatment Outcome